Learning to synthesize: Robust phase retrieval at low photon counts
(PHYSorg.com Physics)

An artifact-free computational approach to extract the phase of light from noisy intensity signals improves imaging of transparent objects, such as biological cells, under low light conditions. The procedure separates intensity signals into high- and low-frequency spectral channels. Deep neural networks are trained to operate on these two frequency bands, before a final algorithm recombines them into a full-band phase image. This method avoids the tendency of automatic phase extraction programs to over-represent low frequencies.